About the Department At Novo Nordisk Research Center Seattle, Inc. (NNRCSI) our scientists apply cutting-edge technologies to early R&D projects with the goal of bringing real change to People with Diabetes and Obesity. Your skills, dedication and ambition will help change lives for the better and you will work with extraordinary talent, continuously learn and develop, and drive changes to defeat serious chronic conditions. We recognize the importance of an enjoyable workplace, which stimulates a strong culture of ingenuity and innovation and our support of a healthy work-life balance adds to a best-in-class employee experience. As a new focus area, we aim to build up a dynamic computational team, which will leverage structure-based design, computational biology and machine learning expertise to the drug discovery process. Our aim is to strengthen target identification and drug design processes at NNRCSI and through global collaboration across our R&D sites. This team will implement state-of-the-art structural modelling and machine learning technologies to improve functional and biophysical properties of proteins, peptides and new molecular format for future therapies. They will build up bioinformatics expertise spanning areas from sequence analysis, computer vision and different omics and pathway analysis. This team will work in a flexible, cross-functional setting in close collaboration with experimentalists to drive pre-clinical projects with very ambitious scientific goals. They will have external collaborations with academic and biotech partners within computational drug discovery in North America. We are changing lives for a living. Are you ready to make a difference? The Position The machine learning scientist will contribute to the Department of Computational Drug Discovery to invent and create the next generation pharmaceuticals through familiarity with state-of-the-art algorithms and experiments within protein and peptide engineering. The machine learning scientist will apply state-of-the-art algorithms to protein and peptide engineering projects across the organization and incorporate experimental results to refine the algorithms. The scientist will analyze, train, and test on experimental results to suggest and design the next experiments in collaboration with scientists across the organization. This role will ensure that the department can execute cutting-edge machine learning algorithms within protein engineering and establish the department as world leading within this field by published articles, patents, or present research. Relationships The machine learning scientist will report to the Director in Computational Drug Discovery. The role will interact with people in various projects as well as departments involved with computational and experimental research as well as IT infrastructure. External stakeholders include, commercial and academic collaborators. Essential Functions Apply state-of-the-art machine learning algorithms within computational drug discovery and optimization by impacting and accelerating projects in the organization Demonstrate ability to combine data from different sources and analyze these Critically evaluate experimental data and incorporate this knowledge into design of experiments to improve predictability and learnings of machine learning algorithms Collaborate with leading external partners from academia and industry to ensure leadership within the field Prepare and present research in top-leading journals or conferences Prepare and present written and oral reports/dashboards to scientists/non-scientists Identify new applications or areas for machine learning within protein and peptide engineering and apply these to improve predictions. Physical Requirements Approximately 0-10% overnight travel. Qualifications PhD required. Degree within machine learning, statistical modeling, computational biology/chemistry/physics, or mathematic modeling or other relevant areas preferred 3+ years of relevant experience required Within 3+ years of relevant experience includes the following: 2+ years of experience with machine learning packages e.g. TensorFlow, Pytorch, sagemaker, etc. 1+ years of experience with setting up workflows from data collection to deployment e.g. AWS Batch 2+ years of experience with cloud or high-performance computing (e.g. AWS, GCP) 2+ years of experience of applying machine learning to protein/peptide engineering or structure prediction either from academia or industry is preferred Publications in the form of high-profile papers or patents within protein/peptide engineering or protein prediction is preferred Working knowledge of bioinformatics and databases is required Experience with scripting languages e.g. python, R etc. preferred Knowledge of analysis of experimental data analysis especially high-throughput and NGS is preferred Ability to work independently and in teams, and to collaborate with external parties Excellent written and oral communication skills Novo Nordisk is an Equal Opportunity Employer - M/F/Veteran/Disability/Sexual Orientation/Gender Identity. If you are interested in applying to Novo Nordisk and need special assistance or an accommodation to apply, please call us at 1-855-411-5290. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.
